We Used a Company Analysis Chatbot to Analyze 50 Unicorns

Which company has a bigger investment in patents – Lyft or Uber? Which tech sector recently suffered from layoffs or legal issues? What kind of newly established companies will face a blue ocean, and who will face a red ocean? Which is investors’ favored industry today, frequently infusing hundreds of millions of dollars, and which one is forgotten, thirsty for money and attention?

In order to answer these questions, one can hire a group of analysts and have them spend a day or two processing data and reviewing the market. However, this time we used the advice of a company analysis chatbot named Emmet to get the information faster.

Meet Emmet: The AI Chatbot for Company Analysis

Emmet is the product of Zirra, a company that built AI-based tools to analyze other companies, currently serving VCs, accredited investors, as well as startups, accelerators and stock exchanges.

Using Emmet (f.k.a Nigel), we get instant smart insights on companies using simple English phrases such as “show me competitors for Uber,” or “opportunities for Github”, or “what are the risks for Airbnb?”.

At this moment, Emmet can produce insights on subjects such as:

-Level of direct competition: Emmet counts up to 20 competitors and evaluates the competition intensity, or the degree of overlap in their offerings. 50% and up is considered as a direct competitor. In our Unicorn analysis, we counted the number of competitors with more than 40% and 50% overlapping offerings.

-Time since last funding: It also calculates how much time has passed since the last funding round for a particular company in units of: 3 months, 6 months, 12 months, two years, three years and longer. A company, or cluster of companies, that has not attracted investors for a substantial amount of time can indicate it is either, 1) suffering from a lack of growth or 2) producing enough cash that allows it to reject investment offers.

-Layoffs: Emmet can detect the occurrences of layoffs that were published in media outlets along with other sources where it is listed on the open web.

-Legal Problems: The chatbot also identifies and determines the total number of legal problems that were published in the media or on litigation websites.

-Patent investment: Normalizing number of patents, Emmet shows them on a scale of 1-5.

To achieve this level of sophistication, Emmet uses a huge array of structured and unstructured data, from multiple sources, and then applies NLP and a variety of A.I. models to analyze companies and markets.

Using direct conversation with Emmet, we analyzed 55 private tech companies (that weren’t being acquired or merged), many of them unicorns, in 11 categories such as ride-hailing apps, self-driving cars or enterprise software. With the help of the tech behind the chatbot we could characterize companies, and clusters of companies, by risk and success criteria, establishing a better notion of their behavior and uniqueness.

Here is the analysis based on the AI chatbot’s findings within some of the reviewed industry segments:

Ride Hailing Apps

Ride Hailing Apps are characterized by a very dynamic funding activity, according to Emmet. In order to keep expanding into new territories, subsidize rides and attract more customers, ride-hailing apps are in constant need of cash. Out of the five companies analyzed here, Uber and Lyft raised hundreds of dollars each in the last three months, while Careem and Ola have done so over the previous six months.

Also, according to the AI chatbot, more ride-hailing apps are in need to create partnerships. Careem, the famous ride-hailing app in Arab countries, announced partnerships with taxi agencies, in-car WiFi providers, and payments services to adapt their service to local communities with local services.

In contrast to what you might have thought about ride-hailing apps, the total number of competitors is low, based on Emmet’s appraisal. After all, how many Ubers and Lyfts are competing for each territory at the same time? However, the intensity of the competition remains rather fierce.

Self-Driving Cars

According to Emmet, self-driving cars technology startups invest in patents, but at an average level that is not so different from most of the startups. Contrary to their innovative, scientific image, their total patent investment is lower even than cybersecurity or adtech firms, in regards to the number of patents.

Food Delivery

Food delivery startups are low on patents but packed with legal issues, according to Zirra’s chatbot.

For example, DoorDash had to pay $5 million to settle a class-action lawsuit that had stated that the company misclassified its employees as independent contractors. Instacart settled a class action lawsuit for $4.6 million after being accused of improper tip pooling and failure to reimburse workers for business expenses.

FinTech

We also found quite a few legal issues in the fintech sector. Disruptive, innovative solutions that collide with the incumbent, traditional banking world is a high-risk potential. In addition, finding new models of dealing with people’s money can create lots of legal issues if not done right.

But not all of these lawsuits go around money. SoFi’s CEO Mike Cagney resigned last September following a sexual harassment lawsuit. Credit Karma was sued by the FTC after disabling security certificates, leaving social users’ data vulnerable to attacks.

In addition, funding activity in the Fintech segment is slow, as most of the companies sampled in this analysis didn’t raise funds for more than a year. Investors have cooled down their enthusiasm about fintech in comparison to 2016 or 2015.

Enterprise Software

However, the most dynamic industry segment we’ve seen so far is in enterprise software. Unicorns in this area are frequently funded, rated high on patent investment and partnership activity. However, they also suffer from a high degree of competition with other companies who have a similar offering, higher than any other industry segment examined in this project. This may also explain the high rate of layoffs in the enterprise software sector.

Are VR, AR and Drones still Trendy?

Other notable tech segments that didn’t raise money recently include drones (19 months on average since prior investment), AR/VR (13 months), and adtech (more than two years). The data supports the fact that AR, VR, and drones are buzzwords that attract less money these days than what it used to be one or two years ago.Flying cars, self-driving cars, and ride-hailing companies were probably much more relevant to investors in 2017.

Adtech

The adtech industry has suffered a blow after it had been accused of creating ad networks and servers that generated profit from an arbitrage in media trading. Consequently, our research shows the industry is highly competitive and experiences layoffs. Investors also have not put their money into this industry for more than two years on average.

Emmet, our chatbot, is just making its first steps into the world of AI-based company analysis.

It’s not perfect but its ability to find critical data and present it within seconds, like no human analyst can do, provides great benefits. Over time, we’ll be adding probabilistic NLP techniques to find new sorts of information, producing more elaborate and accurate insights.

The days when a chatbot will be able to supply analysts and investors with insights needed to make an investment – including private companies – are not far off.

Recognized by the Office of the Chief Scientist in Israel, Zirra is backed by top-tier investors such as Moshe Lichtman, former Corporate VP at Microsoft and now a general partner at IGP, AOL’s Nautilus (now Verizon ventures), Professor Dan Galai, co-inventor of the VIX Index, and Professor Zvi Weiner, Dean of the Business School at the Hebrew University.

Professors Galai and Weiner are both globally recognized researchers in the field of company rating and market risk analysis.